Individual differences in beta-band oscillations predict motor-inhibitory control

Ding, Qi; Lin, Tuo; Cai, Guiyuan; Ou, Zitong; Yao, Shantong; Zhu, Hao; Lan, Yue

doi:10.3389/fnins.2023.1131862

Cited by 9 publications

(4 citation statements)

References 47 publications

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“…Specifically, movement execution during the 'Go' task was associated with a decrease of beta-band power relative to the baseline period (Fixation phase), while movement inhibition during the 'No-go' task was associated with a relative increase of beta-band power. These observed effects are consistent with previous findings about the inhibitory role of the beta-band in other structures of the brain such as the pre-SMA [43], sensorimotor cortex [44], and STN [38,45]. These findings are also in accordance with our previous studies regarding beta-band power modulation in the hippocampus during execution and inhibition of ARMs [22,27].…”

Section: Amygdala During Motor Execution and Inhibitionsupporting

confidence: 93%

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Chung,

Martin del Campo Vera,

Sundaram

et al. 2024

J. Neural Eng.

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IntroductionTraditionally known for its involvement in emotional processing, the amygdala’s involvement in motor control remains relatively unexplored, with sparse investigation into the neural mechanisms governing amygdaloid motor movement and inhibition.ObjectiveThis study aimed to characterize the amygdaloid beta-band (13-30 Hz) power between “Go” and “No-go” trials of an arm reaching task.MethodsTen participants with drug-resistant epilepsy implanted with stereoelectroencephalographic (SEEG) electrodes in the amygdala were enrolled in this study. SEEG data was recorded throughout discrete phases of a Direct Reach Go/No-go task, during which participants reached a touchscreen monitor or withheld movement based on a colored cue. Multitaper power analysis along with Wilcoxon signed-rank and Yates-corrected Z tests were used to assess significant modulations of beta power between the Response and Fixation (baseline) phases in the “Go” and “No-go” conditions.ResultsIn the “Go” condition, nine out of the ten participants showed a significant decrease in relative beta-band power during the Response phase (p ≤ 0.0499). In the “No-go” condition, eight out of the ten participants presented a statistically significant increase in relative beta-band power during the Response phase (p ≤ 0.0494). Four out of the eight participants with electrodes in the contralateral hemisphere and seven out of the eight participants with electrodes in the ipsilateral hemisphere presented significant modulation in beta-band power in both the “Go” and “No-go” conditions. At the group level, no significant differences were found between the contralateral and ipsilateral sides or between genders.ConclusionThis study reports beta-band power modulation in the human amygdala during voluntary movement in the setting of motor execution and inhibition. This finding supplements prior research in various brain regions associating beta-band power with motor control. The distinct beta-power modulation observed between these response conditions suggests involvement of amygdaloid oscillations in differentiating between motor inhibition and execution.

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Section: Amygdala During Motor Execution and Inhibitionsupporting

confidence: 93%

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Chung,

Martin del Campo Vera,

Sundaram

et al. 2024

J. Neural Eng.

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“…Such a relationship between the phase-coupled presentation of stimuli and performance has been shown in other cognitive domains such as sensory perception (Bush et al, 2010;Kasten andHerrmann, 2020), attention (VanRullen, 2018) and memory (Ten Oever et al, 2020). With respect to motor inhibition, stronger coherence in the beta band has been associated with faster inhibitory control (Swann et al, 2012;Ding et al, 2023). However, until now, it was unclear whether inhibitory control performance functionally depends on the phase at which the stop signal is presented.…”

Section: Effect Of Beta Oscillatory Phase On Inhibitory Motor Controlmentioning

confidence: 87%

“…There is concrete evidence suggesting that this inter-regional information exchange is directly related to beta-band oscillatory mechanisms within the fronto-basal ganglia circuit. Intracranial recordings from these regions revealed increased oscillatory activity in the beta frequency band during successful inhibition (Alegre et al, 2013;Kühn et al, 2005;Swann et al, 2009;Swann et al, 2012;Wagner et al, 2018;Wessel and Aron, 2013;Wessel et al, 2016;Castiglione et al, 2019), and this increase in beta activity relates to inhibitory performance (Schaum et al, 2021;Leunissen et al, 2022;Ding et al, 2023). Moreover, the hyperdirect pathway is overactive in Parkinson's disease (PD) (Jahanshahi et al, 2015), resulting in excessive beta oscillations in the STN and cortical motor areas (Brown, 2007), which are associated with bradykinesia, rigidity, and freezing symptoms Little et al, 2012;Chen et al, 2010;Toledo et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition

Fang,

Sack,

Leunissen

2023

Preprint

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Inhibitory control has been linked to beta oscillations in the fronto-basal ganglia network. Here we aim to investigate the functional role of the phase of this oscillatory beta rhythm for successful motor inhibition. We applied 20 Hz transcranial alternating current stimulation (tACS) to the pre-supplementary motor area (pre-SMA) while presenting stop signals at 4 (Experiment 1) and 8 (Experiment 2) equidistant phases of the tACS entrained beta oscillations. Participants showed better inhibitory performance when stop signals were presented at the trough of the beta oscillation whereas their inhibitory control performance decreased with stop signals being presented at the oscillatory beta peak. These results are consistent with the communication through coherence theory, in which postsynaptic effects are thought to be greater when an input arrives at an optimal phase within the oscillatory cycle of the target neuronal population. The current study provides mechanistic insights into the neural communication principles underlying successful motor inhibition and may have implications for phase-specific interventions aimed at treating inhibitory control disorders such as PD or OCD.

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“…In this study, our analysis was specifically focused on the beta frequency band (13-30 Hz), selected for its well-documented role in movement execution and inhibition [77][78][79]. This methodological decision aimed to assess whether the spectral power within the beta band alone could serve as a reliable source for classifiers to discriminate between 'Go' and 'No-go' trials.…”

Section: Classifier Methodsmentioning

confidence: 99%

Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

Martin del Campo Vera,

Sundaram,

Lee

et al. 2024

J. Neural Eng.

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IntroductionCan we decode movement execution and inhibition from hippocampal oscillations during arm-reaching tasks? Traditionally associated with memory encoding, spatial navigation, and motor sequence consolidation, the hippocampus has come under scrutiny for its potential role in movement processing. Stereotactic electroencephalography (SEEG) has provided a unique opportunity to study the neurophysiology of the human hippocampus during motor tasks.ObjectiveIn this study, we assess the accuracy of discriminant functions, in combination with principal component analysis (PCA), in classifying between “Go” and “No-go” trials in a Go/No-go arm-reaching task. Our approach centers on capturing the modulation of beta-band (13-30 Hz) power from multiple SEEG contacts in the hippocampus and minimizing the dimensional complexity of channels and frequency bins.MethodsThis study utilizes SEEG data from the human hippocampus of 10 participants diagnosed with epilepsy. Spectral power was computed during a “center-out” Go/No-go arm-reaching task, where participants reached or withheld their hand based on a colored cue. PCA was used to reduce data dimension and isolate the highest-variance components within the beta band. The Silhouette score was employed to measure the quality of clustering between “Go” and “No-go” trials. The accuracy of five different discriminant functions was evaluated using cross-validation.ResultsThe Diagonal-Quadratic model performed best of the 5 classification models, exhibiting the lowest error rate in all participants (median: 9.91%, average: 14.67%). PCA showed that the first two principal components collectively accounted for 54.83% of the total variance explained on average across all participants, ranging from 36.92% to 81.25% among participants.ConclusionThis study shows that PCA paired with a Diagonal-Quadratic model can be an effective method for classifying between Go/No-go trials from beta-band power in the hippocampus during arm-reaching responses. This emphasizes the significance of hippocampal beta-power modulation in motor control, unveiling its potential implications for brain-computer interface (BCI) applications.

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Individual differences in beta-band oscillations predict motor-inhibitory control

Cited by 9 publications

References 47 publications

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

Beta-band power modulation in the human amygdala differentiates between go/no-go responses in an arm-reaching task

The phase of tACS-entrained pre-SMA beta oscillations modulates motor inhibition

Beta-band power classification of go/no-go arm-reaching responses in the human hippocampus

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